尝试用 pandas 子集替换open()，但是出现__exit__错误? [英] attempting to replace open() with a pandas subset, but I am given an __exit__ error?

问题描述

我正在尝试与pylabels一起为即将发生的事件创建名称标签.在代码的一部分中，有以下tid位:

I am trying to work with pylabels to create nametags for an upcoming event. In one section of the code, there is this tid-bit:

with open(os.path.join(base_path, "names.txt")) as names:
    sheet.add_labels(name.strip() for name in names)

其中sheet = labels.Sheet(specs, write_name, border=True).因此，从本质上讲，这将加载"names.txt"的每一行并使用"specs"中的规范调用函数"write_name"，并将每个名称添加到唯一标签中.我正在尝试将此代码更改为以下代码:

where sheet = labels.Sheet(specs, write_name, border=True). So essentially, this will load each line of "names.txt" and call the function 'write_name', using specifications in 'specs', and add each name to unique labels. I'm attempting to change this code to the following:

with text_file[["Name"]] as names:
    sheet.add_labels(name.strip() for name in names)

但是我得到这个错误:

Traceback (most recent call last):
  File "sticker.V.7.py", line 173, in <module>
    with text_file[["Name"]] as names:
AttributeError: __exit__

有人可以帮助我了解在这种情况下退出的含义吗?其他提交的内容我不明白.

Can anyone help me understand what exit means in this context? I do not understand from other submissions.

我希望添加此子集方面，以便我可以在名称标签中添加更多详细信息.

I am hoping to add this subsetting aspect so that I can add further details to the nametags.

我正在使用Python3.5

I am using Python3.5

推荐答案

有人可以帮助我了解__exit__在这种情况下的含义吗?我从其他意见中看不出来. ... text_file不是函数，因此应该可以退出.

Can anyone help me understand what __exit__ means in this context? I do not understand from other submissions. ... As text_file isn't a function, it should be exitable.

使用 with语句上下文管理器时，则该对象必须定义以下两种方法:

When you use with statement context managers, that object must define these two methods:

• __enter__
• __exit__

• __enter__
• __exit__

无论text_file[["Name"]]是什么(看起来是Pandas DataFrame)，它都不会实现这两种方法.如回溯所示，它根本没有定义__enter__，因此执行从此处停止并引发异常.

Whatever text_file[["Name"]] is (a Pandas DataFrame, it seems), it doesn't implement either of these methods. As indicated by the traceback, it doesn't define __enter__ at all, so execution stops right there and raises an exception.

我认为不需要使用DataFrame作为上下文管理器.一个典型的用例是当您要确保在with块的末尾发生某些事情时，即关闭文件流. (就像try/finally块一样-您想确保__exit__被无条件调用.)对于Pandas DataFrame，我不确定是否有任何类比需要这两个dunder方法.

I don't see a need to use a DataFrame as a context manager. A typical use-case is when you want to ensure that something happens at the end of the with block, namely, closing a file stream. (Like a try/finally block--you want to make sure __exit__ gets called unconditionally.) With a Pandas DataFrame, I'm not sure if there is any analogy that would necessitate have those two dunder methods.

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